Browse Topic: Share transport
The aeromechanics of a full-wing lift-compounded slowed-rotor rotorcraft were investigated experimentally at the Glenn L. Martin Wind Tunnel, characterizing the effects of rotor shaft tilt, wing configuration, and advance ratio on performance, blade structural loads, and hub vibratory loads. Measurements were obtained across advance ratios up to μ=0.7, three shaft tilt angles (-4°, 0°, and 4°), and three wing configurations, including an asymmetric wing arrangement. The results were used to validate the University of Maryland Advanced Rotorcraft Code (UMARC) coupled rotor-wing analysis. Rearward shaft tilt and increased wing lift sharing improved lift-to-drag ratio, reduced blade structural loads, and decreased hub vibratory loads due to the rotor being placed in a descent state and being partially unloaded. Rearward shaft tilt alone yielded a 5% improvement in lift-to-drag ratio and a 32% reduction in steady rotor flap bending moment relative to the forward tilt configuration at an advance ratio of 0.5 and 4° symmetric wing incidence. A peak combined rotor and wing lift-to-drag ratio of 9.6 was achieved at an advance ratio of 0.7 at rearward shaft tilt and with an asymmetric wing incidence configuration, demonstrating the potential of lift compounding for efficient high-speed edgewise rotorcraft flight.
NASA's Space Communications and Navigation (SCaN) Program and the Johns Hopkins Applied Physics Laboratory in Laurel, Maryland, have successfully tested wideband technology that allows spacecraft to communicate with both government and commercial networks for the first time. Launched July 23, 2025, aboard a SpaceX Falcon 9 rideshare mission, the Polylingual Experimental Terminal (PExT) is demonstrating multilingual wideband terminal technology. Hosted on a satellite from York Space Systems, PExT enhances a spacecraft's communications subsystem, enabling mission controllers to track and exchange data more efficiently across a broad range of networks and frequencies.
The advent of EVs, ride sharing, global events such as the pandemic, chip shortage, and increasing dependency on suppliers are just some factors reshaping the automotive business. Consumer sentiment moving from product to experience resulted in more variants being launched at a record pace. Consequently, product development processes need to be more agile and yet more rigorous while bringing about cohesion and alignment across cross-functional teams to launch vehicles on time, on quality, and in budget. Automotive companies have been using Product Lifecycle Management (PLM) solutions for years to manage CAD, change, and BOMs. With changing business scenarios and increasing complexity of products, the sphere of influence of PLM solutions has expanded significantly over the last decade to manage all aspects of product development. Traditionally PLM software focused on integrating with different authoring tools and managing data in a central repository. The PLM solution had multiple such repositories to manage different types of data—CAD, manufacturing, simulation, requirements, engineering changes, and the like. This resulted in additional overhead of synchronizing and replicating this information across these repositories. This approach is not scalable to meet the dynamic needs of product development today. With a significant increase in the scope of PLM, a platform-centric approach that aims to eliminate rather than integrate silos is essential to the successful adoption of PLM software. The answer is next-generation PLM software such as DASSAULT SYSTÈMES ENOVIA PLM on the 3DEXPERIENCE platform that takes a platform-centric approach to managing data, people, and processes. ENOVIA PLM differentiates by being data-driven, eliminates silos, and models business processes that connect the dots throughout the product development process. Dongfeng Automobile Corporation realized 30% efficiency in the design process and 70% decrease in design problems when designing a van with design software and ENOVIA PLM on the 3DEXPERIENCE platform [1].
This paper proposes the use of an on-demand, ride hailed and ride-Shared Autonomous Vehicle (SAV) service as a feasible solution to serve the mobility needs of a small city where fixed route, circulator type public transportation may be too expensive to operate. The presented work builds upon our earlier work that modeled the city of Marysville, Ohio as an example of such a city, with realistic traffic behavior, and trip requests. A simple SAV dispatcher is implemented to model the behavior of the proposed on-demand mobility service. The goal of the service is to optimally distribute SAVs along the network to allocate passengers and shared rides. The pickup and drop-off locations are strategically placed along the network to provide mobility from affordable housing, which are also transit deserts, to locations corresponding to jobs and other opportunities. The study is carried out by varying the behaviors of the SAV driving system from cautious to aggressive along with the size of the SAV fleet and analyzing their corresponding performance. It is found that the size of the network and behavior of AV driving system behavior results in an optimal number of SAVs after which increasing the number of SAVs does not improve overall mobility. For the Marysville network, which is a 9 mile by 8 mile network, this happens at the mark of a fleet of 8 deployed SAVs. The results show that the introduction of the proposed SAV service with a simple optimal shared scheme can provide access to services and jobs to hundreds of people in a small sized city.
Challenges that persons with disabilities face with current modes of transportation have led to difficulties in carrying out everyday tasks, such as grocery shopping and going to doctors’ appointments. Autonomous vehicles have been proposed as a solution to overcome these challenges and make these everyday tasks more accessible. For these vehicles to be fully accessible, the infrastructure surrounding them need to be safe, easy to use, and intuitive for people with disabilities. Thus, the goal of this work was to analyze interview data from persons with disabilities, and their caregivers, to identify barriers to accessibility for current modes of transportation and ways to ameliorate them in pick up/drop off zones for autonomous vehicles. To do this, interview subjects were recruited from adaptive sports clubs, assistive living facilities, and other disability networks to discuss challenges with current public transit stops/stations. Responses to questions were recorded and later analyzed qualitatively and quantitatively to determine 1) common challenges with the current infrastructure around public transit and 2) the number of people who experienced each common challenge. Four challenges were mentioned by nearly every participant: timing or scheduling the transportation, uneven surfaces near the pick up/drop off zone, weather, and steep inclines around the pick up/drop off zone. Each challenge hampered the interview subjects’ ability to access their target vehicle and were mentioned by 90% of the subjects. These challenges informed solutions that could be applied to autonomous vehicle pick up/drop off zones and included on-site ride hailing mechanisms and enclosed, or at least covered, raised platforms with appropriately graded inclines. These solutions were explored using design software. Challenges with current transportation infrastructure were identified in this work, and their respective solutions can help ensure that future autonomous vehicles are accessible to persons with disabilities, a population for whom they have significant benefit.
The changing mobility landscape of India reveals that the erstwhile transport modes of the 20th century i.e., railways and road buses are making way for airlines, personal vehicles, shared mobility, metro rails. Rapid technological changes, stricter regulations, new transport cultures autonomous, connected, electric and shared (ACES), state-of-the-art and environmental concerns are shaping up the eco-system for automobiles. Despite these challenges roadways and automobiles will continue to be most prominent solution in India for future. But for that, the automobile sector should be agile, innovative, and adaptable to changing eco-system, vigilant to thwart threat of alternate mobility solutions and must provide sustainable solutions for the future. The purpose of this paper to evaluate various mobility solutions, ascertain prominence of upcoming automobile solutions and their sustainability for future in India. A systems engineering approach has been adopted to the eco-system influencing sustainable automobile solutions, for identifying the key attributes (drivers and barriers) and validating the resultant V-model. Data was collected from extensive literature review and questionnaire surveys conducted in India and a hybrid MCDM (multi criteria decision making) technique, suitable for the hierarchical and interdependent attributes, was adopted to arrive at the rankings of the key attributes in relation to sustainable automobile solutions.
One-way car-sharing services (CSSs) are believed to be a promising transportation mode for urban mobility. Due to the disparity of city functional areas and population, travel demand and vehicle supply in a CSS may inevitably tend to be imbalanced as well. Therefore, an essential requirement of one-way CSSs is the capability of providing fleet management solutions to improve quality of service and system performance. In other words, a CSS depends heavily on technologies that offer strategic decisions on topics like Fleet sizing Location and capacity of depots and charging stations Matching of travelers with vehicles Relocation of vehicles and dispatchers for fleet rebalancing Balancing and charging schedules of electric vehicles Car-sharing Mobility-on-Demand Systems addresses trending CSS technologies and outlines some insights into the existing unsettled issues and potential solutions. The discussions and outlook are presented as a collection of key points encountered in system planning, configuration, and especially fleet operation. In doing so, the focus is on innovation in technologies, policies, operations, and regulations that impact operators, users, and transport management authorities. Click here to access the full SAE EDGETM Research Report portfolio.
Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining questions about how to implement and regulate FRS in a way that maximizes its safety and security potential while simultaneously ensuring individual’s right to privacy, data security, and technology-based equality. Legal Issues Facing Automated Vehicles, Facial Recognition, and Individual Rights seeks to highlight the benefits of using FRS in public and private transportation technology and addresses some of the legitimate concerns regarding its use by private corporations and government entities, including law enforcement, in public transportation hubs and traffic stops. Constitutional questions, including First, Forth, and Ninth Amendment issues, also remain unanswered. FRS is now a permanent part of transportation technology and society; with meaningful legislation and conscious engineering, it can make future transportation safer and more convenient. Click here to access the full SAE EDGETM Research Report portfolio.
A single main rotor helicopter with a wing is one proposed design for the U.S. Army Future Vertical Lift (FVL) Capability Set 1 (CS-1). While there are many single main rotor aircraft, there are a few with stub wing designs and even fewer with a large wing appropriate for high speed operating conditions expected for FVL. In this work, a flight dynamics model of generic single main rotor helicopter with a wing is designed to meet the FVL CS-1 class of aircraft. The generic design is derived from open literature and well studied UH-60A, Bo-105, and XV-15 aircraft. The design is implemented in a blade element flight dynamics model which is subsequently used to develop a preliminary flight control design. The complete aircraft design approach is detailed and design tradeoffs with respect to trim, flight dynamics, and maneuverability are presented.
Shared mobility will become an important part in the future smart transportation and contribute to sustainable development. However, recently a large number of pioneers in this market have failed in making profits, and have to declare bankrupt or give up this promising business. One main cause is that it is difficult to find a method to allocate the profits to all the partners reasonably. In other words, there is still no effective business model in smart mobility. This study discusses cooperation among all stakeholders, including four species of participants, in smart mobility business alliance based on the theory of community ecology. The leaders are the enterprises who offer business platforms for the other players. The enablers include OEMs, hardware and software suppliers who contribute to smart mobility with intelligent vehicle products and technologies. The supporters can provide infrastructure and market channels. And the parasites are able to create added value with services and contents on basis of the platforms and products from other species. This paper establishes a cooperative game model composed of profit functions for all the stakeholders, considering both car sharing and private travel in the era of intelligent vehicles. A profit distribution strategy is proposed with Shapley value method, which ensures the efficiency and fairness. A quantitative analysis based on Chinese market data is conducted. The results indicate that the leaders and enablers will gain the most of the benefits of smart mobility, accounting for more than 80 percent. The cooperation improves the whole profits by around 60 percent, compared to the situation in which each species operates alone. Thus, the supporters and parasites who can benefit more from cooperation should assist in developing the market and reducing the operating costs of the whole business alliance.
The development of carsharing can reduce the number of private cars, which can save resources. Due to the limited supply of vehicles and diversified demands of users, it is necessary to plan the temporal and spatial distribution of cars. Predicting the pick-up time of carsharing users is of great significance to understand the travel preference of carsharing users, which can help operators formulate operational strategies such as relocation and pricing. To this end, this study adopts an improved decision tree (DT) to analyze and predict pick-up time for carsharing users. Firstly, the ordered clustering method is used to discretize time. Secondly, the random forest (RF) model is constructed to extract key features. Finally, the model of the C5.0 DT is constructed to predict the pick-up time of users. A case study is conducted to demonstrate the proposed model. The results indicate that the prediction accuracy of users’ pick-up time can reach 87%. The characteristic of pick-up time of carsharing users is clearly analyzed.
This SAE Recommended Practice provides a taxonomy of terms related to local and regional on-demand and shared mobility services (including ground, aviation, and maritime) and their enabling technologies. Functional definitions for shared modes (both fleet sharing and ride services), services, business models, and mobility applications are defined in this SAE Recommended Practice. This SAE Recommended Practice also provides a taxonomy of related terms and definitions. Though public transport is part of shared mobility, it is not included in this SAE Recommended Practice because its definition is well-established and documented. This document does not provide specifications or otherwise impose requirements on on-demand and shared mobility.
In a photocatalytic air purifier system, the catalyst that cleans the air is typically titanium dioxide and it is energized by ultraviolet (UV) light. When UV light shines on the titanium dioxide, electrons (negatively charged particles inside atoms) are released at its surface. The electrons interact with water molecules (H2O) in the air, breaking them up into hydroxyl radicals (OH·), 9which are highly reactive, short-lived, uncharged forms of hydroxide ions (OH−). These small, agile hydroxyl radicals then attack bigger organic (carbon-based like virus) pollutant molecules, breaking apart their chemical bonds and turning them into harmless substances such as carbon dioxide and water. Current investigation uses the above principle to kill living organic germs, bacteria; pathogen, etc. from the cabin air in recirculation mode. A HVAC system has been developed by using a filter impregnated by titanium di-oxide (TiO2) with UV lights to improve and maintain cabin air quality. The developed system has been developed to kill virus, germs, pathogens and bacteria that typically exist in a conditioned space. The designed system can be used for conventional vehicles, EVs, ride sharing and for autonomous vehicles. Tests were conducted at a certified laboratory with MS2, a bacteriophage size of 0.027 microns. MS2 is a proxy for SARS-CoV-2, the virus that causes COVID-19 with a size of 0.125 microns. Effectiveness of the destruction rate was determined for the developed system. Detailed summary will be presented in the paper.
A new type of electric brake booster, which can control brake pedal feeling completely with software, has been developed to explore how a brake system can be used to differentiate and personalize vehicles. In the future, vehicles may share an increasing amount of hardware and rely more heavily on software to differentiate between models. Car sharing, vehicle subscriptions, and other new business models may create a new emphasis on the personalization of vehicles that may be achieved most cost effectively by using software. This new brake booster controls the brake pedal force and brake pressure independently based on the brake pedal stroke so that the pedal feeling is completely defined by software. The booster uses two electric motors and one master cylinder. One electric motor controls the pedal force and provides an assist force that amplifies the force that the driver applies to the brake pedal. The second electric motor moves the master cylinder piston independently of the brake pedal stroke and is used to control the brake pressure. To confirm the real-world feasibility of this concept, the booster was installed in an actual vehicle. The evaluation of this vehicle confirmed that software-defined pedal feeling is feasible to implement in a real vehicle. Pedal feeling as good as that of a mass produced vehicle could be achieved, and the pedal feeling could be quickly and easily changed without the time and expense required to change brake hardware. Additionally, using this new booster, new types of pedal feeling that are not possible to achieve on a conventional vacuum booster vehicle could be easily implemented with software.
Sharing mobility has led to a reduction of car ownership with consequent decrease in impacts from a multiple economic, social and environmental perspective. One way of promoting sustainable mobility is to establish the use of electric vehicles (EVs), but insufficient knowledge and high uncertainty towards EV technology can represent a barrier to the acceptance of these new forms of mobility. Under-thirty are recognized as a prospective customer group for car sharing services, very receptive to technological innovation. Based on this premise, the study proposed a double-structured methodological framework to investigate university student user profile defining the heterogeneous preferences regarding a mix of attributes of the service design and to assess the impact of car-sharing experience on acceptance of EVs. Preferences for specific service attributes have been explored (e.g. rate, different power systems) and possible predictors have been tested (e.g. car ownership, neighborhood walkability, ecological awareness) by using a quantitative analysis with car-sharing users and non-users. This methodology has been implemented in the city of Enna (Italy), where university population constitute a high percentage of residents and a recent station-based car sharing service has been implemented. Besides the demographics characteristics, the students’ demand of mobility and acceptance of EVs have been investigated through a survey data analysis, considering several operational attributes and context-related variables in applying Likert scale. The results show that experience in using, EV vehicles leads to higher acceptance of this new technology. Furthermore, it emerged a correlation between gender distribution and operating and infrastructural characteristics of the service, like the presence of reserved parking with charging stations. This study lays the basis for more in-depth research for service design and reconversion through the introduction of shared EVs, improving their use both for home-school and home-leisure trips and discouraging the use of the private vehicle.
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